Real-time anti-poaching tags could help prevent imminent species extinctions

Establishing bio-logging data collections as dynamic archives of animal life on Earth

Rapid growth in bio-logging-the use of animal-borne electronic tags to document the movements, behaviour, physiology and environments of wildlife-offers opportunities to mitigate biodiversity threats and expand digital natural history archives. Here we present a vision to achieve such benefits by accounting for the heterogeneity inherent to bio-logging data and the concerns of those who collect and use them. First, we can enable data integration through standard vocabularies, transfer protocols and aggregation protocols, and drive their wide adoption. Second, we need to develop integrated data collections on standardized data platforms that support data preservation through public archiving and strategies that ensure long-term access. We outline pathways to reach these goals, highlighting the need for resources to govern community data standards and guide data mobilization efforts. We propose the launch of a community-led coordinating body and provide recommendations for how stakeholders-including government data centres, museums and those who fund, permit and publish bio-logging work-can support these efforts.

Time synchronisation for millisecond-precision on bio-loggers

Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies.We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony.During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range.Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.

Perspectives in machine learning for wildlife conservation

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into relevant information. We argue that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge. Incorporating machine learning into ecological workflows could improve inputs for ecological models and lead to integrated hybrid modeling tools. This approach will require close interdisciplinary collaboration to ensure the quality of novel approaches and train a new generation of data scientists in ecology and conservation.

Noninvasive Technologies for Primate Conservation in the 21st Century

Observing and quantifying primate behavior in the wild is challenging. Human presence affects primate behavior and habituation of new, especially terrestrial, individuals is a time-intensive process that carries with it ethical and health concerns, especially during the recent pandemic when primates are at even greater risk than usual. As a result, wildlife researchers, including primatologists, have increasingly turned to new technologies to answer questions and provide important data related to primate conservation. Tools and methods should be chosen carefully to maximize and improve the data that will be used to answer the research questions. We review here the role of four indirect methods—camera traps, acoustic monitoring, drones, and portable field labs—and improvements in machine learning that offer rapid, reliable means of combing through large datasets that these methods generate. We describe key applications and limitations of each tool in primate conservation, and where we anticipate primate conservation technology moving forward in the coming years.

Timely poacher detection and localization using sentinel animal movement

Wildlife crime is one of the most profitable illegal industries worldwide. Current actions to reduce it are far from effective and fail to prevent population declines of many endangered species, pressing the need for innovative anti-poaching solutions. Here, we propose and test a poacher early warning system that is based on the movement responses of non-targeted sentinel animals, which naturally respond to threats by fleeing and changing herd topology. We analyzed human-evasive movement patterns of 135 mammalian savanna herbivores of four different species, using an internet-of-things architecture with wearable sensors, wireless data transmission and machine learning algorithms. We show that the presence of human intruders can be accurately detected (86.1% accuracy) and localized (less than 500 m error in 54.2% of the experimentally staged intrusions) by algorithmically identifying characteristic changes in sentinel movement. These behavioral signatures include, among others, an increase in movement speed, energy expenditure, body acceleration, directional persistence and herd coherence, and a decrease in suitability of selected habitat. The key to successful identification of these signatures lies in identifying systematic deviations from normal behavior under similar conditions, such as season, time of day and habitat. We also show that the indirect costs of predation are not limited to vigilance, but also include (1) long, high-speed flights; (2) energetically costly flight paths; and (3) suboptimal habitat selection during flights. The combination of wireless biologging, predictive analytics and sentinel animal behavior can benefit wildlife conservation via early poacher detection, but also solve challenges related to surveillance, safety and health.

Machine learning enables improved runtime and precision for bio-loggers on seabirds

Unravelling the secrets of wild animals is one of the biggest challenges in ecology, with bio-logging (i.e., the use of animal-borne loggers or bio-loggers) playing a pivotal role in tackling this challenge. Bio-logging allows us to observe many aspects of animals’ lives, including their behaviours, physiology, social interactions, and external environment. However, bio-loggers have short runtimes when collecting data from resource-intensive (high-cost) sensors. This study proposes using AI on board video-loggers in order to use low-cost sensors (e.g., accelerometers) to automatically detect and record complex target behaviours that are of interest, reserving their devices’ limited resources for just those moments. We demonstrate our method on bio-loggers attached to seabirds including gulls and shearwaters, where it captured target videos with 15 times the precision of a baseline periodic-sampling method. Our work will provide motivation for more widespread adoption of AI in bio-loggers, helping us to shed light onto until now hidden aspects of animals’ lives.

Joseph Korpela et al. demonstrate the use of machine-learning assisted bio-loggers on black-tailed gulls and streaked shearwaters. As video recording is only activated through variations in movement detected by low-cost accelerometers, this method represents improvements to runtime and precision over existing bio-logging technology.

The perfect threat: Pesticides and vultures

Probably the most important threat currently affecting vultures worldwide is exposure to pesticides, both accidentally and through deliberate abuse. This is of special concern since around 70% of vulture species are threatened by human activities. However, information about this threat is sparse and geographically biased. We compiled existing knowledge about pesticide exposure in vulture species globally, providing unifying criteria to mitigate this problem with a joint global effort. Most information available about accidental exposure to pesticides in vultures is related to organochlorine pesticides. Non-lethal exposure to these compounds occurs on every continent that vultures inhabit. While concentrations of organochlorine pesticides reported in different samples appear to be too low to produce health impacts, some studies show vultures with levels compatible with health impacts. In addition, there are some reports of vultures contaminated accidentally by anticoagulant rodenticides and external antiparasitic drugs used in veterinary practices. Deliberate abuse of pesticides to poison wildlife also occurs on every continent where vultures live, affecting most (78%) vulture species. However, little information is available for some regions of America, Asia and Europe. The exact number of vultures killed due to deliberate poisoning with pesticides is not well known, but the available figures are alarming (e.g. up to 500 individuals in a single event). The most widely used pesticides affecting vulture populations, and associated with deliberate poisoning, are carbamates and organophosphorus compounds. Of particular concern is the fact that massive poisoning events with these compounds occur, in some cases, within protected areas. This suggests that if this situation is not reversed, some vulture populations could disappear. A combination of measures such as banning pesticides, controlling their distribution-acquisition and environmental education could produce better results that banning pesticides alone. If poisoning with pesticides is not stopped, this threatened avian group could inadvertently go extinct very soon.

Classifying elephant behaviour through seismic vibrations

Seismic waves - vibrations within and along the Earth's surface - are ubiquitous sources of information. During propagation, physical factors can obscure information transfer via vibrations and influence propagation range [1]. Here, we explore how terrain type and background seismic noise influence the propagation of seismic vibrations generated by African elephants. In Kenya, we recorded the ground-based vibrations of different wild elephant behaviours, such as locomotion and infrasonic vocalisations [2], as well as natural and anthropogenic seismic noise. We employed techniques from seismology to transform the geophone recordings into source functions - the time-varying seismic signature generated at the source. We used computer modelling to constrain the propagation ranges of elephant seismic vibrations for different terrains and noise levels. Behaviours that generate a high force on a sandy terrain with low noise propagate the furthest, over the kilometre scale. Our modelling also predicts that specific elephant behaviours can be distinguished and monitored over a range of propagation distances and noise levels. We conclude that seismic cues have considerable potential for both behavioural classification and remote monitoring of wildlife. In particular, classifying the seismic signatures of specific behaviours of large mammals remotely in real time, such as elephant running, could inform on poaching threats.

Optimizing the use of biologgers for movement ecology research

The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored. Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF). We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology. We focus on the importance of efficient data exploration, and more advanced multidimensional visualization methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by biologging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data. Taking advantage of the biologging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high-frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location-only technology such as GPS. Equally important will be the establishment of multidisciplinary collaborations to catalyse the opportunities offered by current and future biologging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes and for building realistic predictive models.

Patterns of satellite tagged hen harrier disappearances suggest widespread illegal killing on British grouse moors

Identifying patterns of wildlife crime is a major conservation challenge. Here, we test whether deaths or disappearances of a protected species, the hen harrier, are associated with grouse moors, which are areas managed for the production of red grouse for recreational shooting. Using data from 58 satellite tracked hen harriers, we show high rates of unexpected tag failure and low first year survival compared to other harrier populations. The likelihood of harriers dying or disappearing increased as their use of grouse moors increased. Similarly, at the landscape scale, satellite fixes from the last week of life were distributed disproportionately on grouse moors in comparison to the overall use of such areas. This pattern was also apparent in protected areas in northern England. We conclude that hen harriers in Britain suffer elevated levels of mortality on grouse moors, which is most likely the result of illegal killing.

Tackling wildlife crimes requires determining their occurrence and distribution, but they are often difficult to detect. Here, the authors use hen harrier tracking data to show patterns of unexpected tag failure that suggest widespread illegal killing on moors managed for recreational shooting of red grouse.

Bears habituate to the repeated exposure of a novel stimulus, unmanned aircraft systems

Unmanned aircraft systems (UAS; i.e. 'drones') provide new opportunities for data collection in ecology, wildlife biology and conservation. Yet, several studies have documented behavioral or physiological responses to close-proximity UAS flights. We experimentally tested whether American black bears (Ursus americanus) habituate to repeated UAS exposure and whether tolerance levels persist during an extended period without UAS flights. Using implanted cardiac biologgers, we measured heart rate (HR) of five captive bears before and after the first of five flights each day. Spikes in HR, a measure of stress, diminished across the five flights within each day and over the course of 4 weeks of twice-weekly exposure. We halted flights for 118 days, and when we resumed, HR responses were similar to that at the end of the previous trials. Our findings highlight the capacity of a large mammal to become and remain habituated to a novel anthropogenic stimulus in a relatively short time (3-4 weeks). However, such habituation to mechanical noises may reduce their wariness of other human threats. Also, whereas cardiac effects diminished, frequent UAS disturbances may have other chronic physiological effects that were not measured. We caution that the rate of habituation may differ between wild and captive animals: while the captive bears displayed large initial spikes in HR change (albeit not as large as wild bears), these animals were accustomed to regular exposure to humans and mechanical noises that may have hastened habituation to the UAS.

The illegal pet trade is driving Madagascar's ploughshare tortoise to extinction

The illegal wildlife trade is driving declines in populations of a number of large, charismatic animal species but also many lesser known and restricted-range species, some of which are now facing extinction as a result. The ploughshare tortoise Astrochelys yniphora, endemic to the Baly Bay National Park of north-western Madagascar, is affected by poaching for the international illegal pet trade. To quantify this, we estimated population trends during 2006–2015, using distance sampling surveys along line transects, and recorded national and international confiscations of trafficked tortoises for 2002–2016. The results suggest the ploughshare tortoise population declined > 50% during this period, to c. 500 adults and subadults in 2014–2015. Prior to 2006 very few tortoises were seized either in Madagascar or internationally but confiscations increased sharply from 2010. Since 2015 poaching has intensified, with field reports suggesting that two of the four subpopulations are extinct, leaving an unknown but almost certainly perilously low number of adult tortoises in the wild. This study has produced the first reliable population estimate of the ploughshare tortoise and shows that the species has declined rapidly because of poaching for the international pet trade. There is an urgent need for increased action both in Madagascar and along international trade routes if the extinction of the ploughshare tortoise in the wild is to be prevented.

Poaching Detection Technologies-A Survey

Between 1960 and 1990, 95% of the black rhino population in the world was killed. In South Africa, a rhino was killed every 8 h for its horn throughout 2016. Wild animals, rhinos and elephants, in particular, are facing an ever increasing poaching crisis. In this paper, we review poaching detection technologies that aim to save endangered species from extinction. We present requirements for effective poacher detection and identify research challenges through the survey. We describe poaching detection technologies in four domains: perimeter based, ground based, aerial based, and animal tagging based technologies. Moreover, we discuss the different types of sensor technologies that are used in intruder detection systems such as: radar, magnetic, acoustic, optic, infrared and thermal, radio frequency, motion, seismic, chemical, and animal sentinels. The ultimate long-term solution for the poaching crisis is to remove the drivers of demand by educating people in demanding countries and raising awareness of the poaching crisis. Until prevention of poaching takes effect, there will be a continuous urgent need for new (combined) approaches that take up the research challenges and provide better protection against poaching in wildlife areas.

A clear and present danger: impacts of poisoning on a vulture population and the effect of poison response activities

Vultures in Africa are being poisoned deliberately by poachers to prevent the birds alerting authorities to the poachers’ illegal activities, or for harvesting and sale of body parts for use in witchcraft. Hundreds of vultures can be killed at a single poisoned elephant Loxodonta africana carcass, and although field staff trained in poison response activities can limit the damage, mortalities remain numerous. We used the population viability analysis programme VORTEX to simulate seven 100-year-long scenarios investigating various rates of poisoning mortalities and the remedial effects of poison response activities on a population of Critically Endangered white-backed vultures Gyps africanus breeding in Kruger National Park, South Africa. In six scenarios the population declined (λ < 1); in three scenarios the population remained extant over the 100-year simulations but declined by 60–90% from a starting size of 2,400 individuals. In two scenarios one poisoned elephant carcass left untreated and causing the greatest number of vulture deaths was modelled as a catastrophic event with a 50% probability of annual occurrence, which resulted in a 100% probability of population extinction, with a mean time to extinction of 55–62 years. Effective poison response activities were modelled as a 70% reduction of mortality at each poisoned elephant carcass and resulted in population persistence after 100 years but with a c. 90% reduction in size (final n = 205). We highlight that although poison response activities will not prevent poisoning from occurring, they form an essential part of wider conservation actions designed to prevent local extinctions of vultures or other vulnerable species.

Impending extinction crisis of the world's primates: Why primates matter

Nonhuman primates, our closest biological relatives, play important roles in the livelihoods, cultures, and religions of many societies and offer unique insights into human evolution, biology, behavior, and the threat of emerging diseases. They are an essential component of tropical biodiversity, contributing to forest regeneration and ecosystem health. Current information shows the existence of 504 species in 79 genera distributed in the Neotropics, mainland Africa, Madagascar, and Asia. Alarmingly, ~60% of primate species are now threatened with extinction and ~75% have declining populations. This situation is the result of escalating anthropogenic pressures on primates and their habitats-mainly global and local market demands, leading to extensive habitat loss through the expansion of industrial agriculture, large-scale cattle ranching, logging, oil and gas drilling, mining, dam building, and the construction of new road networks in primate range regions. Other important drivers are increased bushmeat hunting and the illegal trade of primates as pets and primate body parts, along with emerging threats, such as climate change and anthroponotic diseases. Often, these pressures act in synergy, exacerbating primate population declines. Given that primate range regions overlap extensively with a large, and rapidly growing, human population characterized by high levels of poverty, global attention is needed immediately to reverse the looming risk of primate extinctions and to attend to local human needs in sustainable ways. Raising global scientific and public awareness of the plight of the world's primates and the costs of their loss to ecosystem health and human society is imperative.

Local Perspectives on Environmental Insecurity and Its Influence on Illegal Biodiversity Exploitation

Environmental insecurity is a source and outcome of biodiversity declines and social conflict. One challenge to scaling insecurity reduction policies is that empirical evidence about local attitudes is overwhelmingly missing. We set three objectives: determine how local people rank risk associated with different sources of environmental insecurity; assess perceptions of environmental insecurity, biodiversity exploitation, myths of nature and risk management preferences; and explore relationships between perceptions and biodiversity exploitation. We conducted interviews (N = 88) with residents of Madagascar's Torotorofotsy Protected Area, 2014. Risk perceptions had a moderate effect on perceptions of environmental insecurity. We found no effects of environmental insecurity on biodiversity exploitation. Results offer one if not the first exploration of local perceptions of illegal biodiversity exploitation and environmental security. Local people's perception of risk seriousness associated with illegal biodiversity exploitation such as lemur hunting (low overall) may not reflect perceptions of policy-makers (considered to be high). Discord is a key entry point for attention.